1. Technical Field
The present disclosure relates to data processing, and in particular, to presenting information to users.
2. Description of the Related Art
Unless otherwise indicated herein, the approaches described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
Huge amounts of textual information relevant for market analysis, trending or product monitoring can be found on the Web. Analysts estimate that up to 80% of all business relevant information within companies and on the web is stored as unstructured textual documents. Being able to exploit such information (for example, for market analysis, trending, or web monitoring) is a competitive advantage for companies.
To make use of that information, a number of text mining techniques exist that extract and categorize entities from given text. These techniques include the classification of text documents, the recognition of entities and relationships as well as the identification of sentiments. Recently, many of these text mining techniques were made publicly available as web services (e.g., OpenCalais, AlchemyAPI, etc.) to simplify their consumption and application integration. Individual services often have specific strengths and weaknesses.